Methods and systems for speech detection

ABSTRACT

Methods and systems for processing user input to a computing system are disclosed. The computing system has access to an audio input and a visual input such as a camera. Face detection is performed on an image from the visual input, and if a face is detected this triggers the recording of audio and making the audio available to a speech processing function. Further verification steps can be combined with the face detection step for a multi-factor verification of user intent to interact with the system.

RELATED APPLICATIONS

This application is a continuation application of co-pendingInternational Patent Application No. PCT/EP2018/078469, filed Oct. 18,2018, which claims the benefit of priority from EP Patent ApplicationNo. 17197186.4 filed Oct. 18, 2017, which is herein incorporated byreference.

TECHNICAL FIELD

This invention relates to the field of speech processing, and inparticular to speech detection.

BACKGROUND ART

Interactions that require a user to talk include requiring a user toread text, or to identify/talk about an image or in response to a visualprompt, to copy an audio prompt, to translate audio/text, to answer aquestion, or to engage in a ‘conversation’. Other interactions andapplications include voice search, interaction with navigation systems,game control, dictation, voice instructions, or general voice inputfunctionality of any system.

For any such speech recognition system, there is a challenge in knowingwhen a user is trying to use the system.

One solution is to implement an “always listening” functionality. Thesystem continuously “listens” (i.e. processes audio input) for a ‘wakeword’ like ‘Alexa’ or ‘OK Google’. This is controversial as users maybelieve that the system could be processing, transferring ortranscribing all the audio it picks up.

In recent years there have in fact been several instances where devicessuch as television sets (smart TVs) have been found to be doing justthis, collecting user speech data which is transferred back to themanufacturer or given to third parties. References to “Big Brother” areapt,

The unauthorised collection of speech data is a major concern forconsumers and can damage their trust in devices. Concerns relate toprivacy and to data protection. Where the speech data includeschildren's speech, the concerns are increased. Lawsuits have been filedagainst toymakers arising from the unlimited collection of speech datafrom children, for whom parental consent has not been obtained.

Apart from those concerns, the “always listening” approach, with orwithout a predefined wake word, is highly inefficient. It involvescollecting and processing useless audio, which is expensive for thesystem, occupying processors and running down the battery.

More efficient approaches involve a prompt to a user at the time thataudio processing is activated, or user indication of intention tointeract.

The prompt approach will typically use a display (for example theappearance of an icon, a text prompt, or the highlighting of the screenor an area of the screen, to visually to indicate to the user when tobegin speaking. This approach often fails as it does not take intoaccount any user intent or readiness.

The user indication of intention to interact is typically implementedvia a button press (physical or soft button). The button can be “pressto talk” where the system listens and processes data for as long as thebutton is held down, or “tap to talk” where the user taps once to startand taps again to stop the system listening. Whichever of theseapproaches is adopted, there are disadvantages. For children, buttonpresses can be difficult to comply with, and frequently fail because thechild is unable to properly coordinate the actions (press the button,wait a short period for the system to be ready, then start to speak).

DISCLOSURE OF THE INVENTION

There is provided in one aspect, a method of processing user input to acomputing system having an audio input and a visual input, comprisingthe steps of:

-   -   providing a visual or auditory prompt to a user of the computing        system;    -   performing a face detection method on an image received from the        visual input after the visual or auditory prompt has been        provided; and    -   responsive to a determination that said face detection method        has detected a face within a predetermined time of the visual or        auditory prompt having been provided:        -   recording an audio signal from said audio input; and        -   making said audio signal available to a speech processing            function.

By employing face detection as a necessary precondition and trigger forthe recording and processing of audio signals, the issue of userintention is addressed to a large degree. If the system does not detecta user's face, it will not record an audio signal and make it availablefor speech processing. This provides significant advantages to the user,in that it prevents casual audio being recorded when a face is notdetected. When implemented in a handheld device such as a mobile phone,face detection provides a strong indicator of user intention tointeract.

By combining face detection with the provision of a prompt to the user,the intentionality is greatly strengthened. Furthermore, the particularcombination of a user prompt combined with face detection solves aparticular problem where the user is a small child, or has compromiseddexterity or is unable to manually interact with a system. Unlikesystems that are always on—processing video data to detect a facecontinually, with consequent impact on power usage and backgroundprocessing requirements—the current system only needs to perform facedetection for a predetermined period of time following the prompt.Similarly, there is an economy of processing and power as compared tosystems relying on a “wake word” (“OK Google” or “Hey Alexa” beingcurrent examples). Finally, unlike systems that are only active when theuser presses a button (“tap to speak”) to trigger either speechprocessing or face detection, the user is not required to havedexterity, physical proximity, or (particularly in the case of youngchildren) the understanding and control required to sequence and timethe button press to the speech input. The visual input is preferably acamera, which can be local to the device which is recording (andoptionally processing) the audio, or it can be located remotely from therecording device. Image processing may be performed on still images oron video images, streams or files, and terms such as “image” or “imageprocessing” are intended to encompass both still and moving images. Theface detection can be achieved not only by processing conventionalcamera images, but also by infrared detectors, by thermal imaging, bylaser interrogation, or in any other suitable manner.

The method can be implemented in a distributed fashion, with differentelements of the system, responsible for different functionality,provided in different devices. A common implementation is to have facedetection and audio capture local to a single user device, with audiobeing streamed to a remote system for recording and processing.

The predetermined time within which the determination of the detectionof a face should be made, following the visual or auditory prompt havingbeen provided, may be implemented as an absolute value (e.g. within xnumber of seconds of the start or end of the prompt), or dynamicallyaccording to the complexity of the prompt, the ability of the user, orlearned behaviour. It can be tied to the operation of software providingthe prompt (e.g. while a visual prompt is displayed on screen) or to theoperation of some other aspect of the device (e.g. while an app isactive or in focus, or until a screen timeout occurs or the user locksthe device). The skilled person will readily find other examples. Theimportant aspect is that the face detection is limited to and associatedwith the prompt so that it provides a good signal of intentionality tointeract with the device or system.

Preferably, the method involves performing one or more additionalverification steps, wherein the steps of recording an audio signal andmaking said audio signal available are dependent on the outcome of saidone or more further verification steps in addition to said facedetection method detecting a face.

In this way a multi-factorial determination can be made, not relying onface detection alone. The particular choice of which additionalverification steps will often be determined by the application. Forexample, a user of a language learning system who is expected to saywhat is onscreen or to read (or translate) a visual prompt, would bestrongly expected to be looking at the screen. On the other hand, a userof a car's navigation system or some other voice interface would not beexpected to be looking at the screen to the same extent.

It can be hard to know what context the user means when they speak. Thiscan be particularly the case where there might be multiple items in thefield of view of the user that could react to a voice interaction. Forexample, the user might be presented with multiple items on a screen andwant to action just one of them. There might be several devices (homedevices, smart devices, smart toys or robots) available for interaction.In the case of virtual reality, mixed reality or augmented reality therecould be multiple items in the VR/MR/AR overlay seen by a user as wellas in the real world environment of the user. Eye tracking, using acamera on the device or on eyewear worn by the user, to determinewhere/what the user is looking at. When the user gives a voice commandthe event is triggered for that item or area in the user's focus.

Accordingly in suitable circumstances, the one or more additionalverification steps may comprise a gaze direction detection step toverify that the user is looking in a predefined direction or range ofdirections.

Additionally or alternatively, the one or more additional verificationsteps may comprise a mouth movement detection step to verify that theuser's mouth is moving.

Optionally, the mouth movement detection step further verifies that themouth movement of the user corresponds to a movement pattern typical ofspeech.

Optionally, the one or more additional verification steps comprise anaudio detection step to verify that the audio input is receiving soundfrom the environment of the user.

Such audio detection or processing may involve temporary buffering orrecording of the audio input, which is to be distinguished from thesubsequent recording of a signal in response to a successfuldetermination of user intent, for use in subsequent processing. A looseanalogy can be made with the distinction between how a processor maytemporarily store in memory the variables and data required for acurrent operation and the writing of data and variables to disk storage.

Optionally, the audio detection step further verifies that thecharacteristics of detected sound are consistent with speech.

This may be as simple or as sophisticated as the designer of the systemwishes. Relatively basic filters can be used to distinguish betweensound that is of similar frequency range to speech and sound that isnon-speech noise, for example, or a more sophisticated audio processingsystem can be used to more reliably ensure that the detected sound isvery likely to be speech.

Optionally, the audio detection step further verifies that the directionfrom which sound is detected is consistent with the direction of thedetected face.

Thus if the audio input is a microphone (or plurality of microphones)with directional capabilities, the sound may be associated (or not) withthe visual field in which a face was detected.

In another optional implementation, the audio detection step furtherverifies that the characteristics of detected sound are consistent witha speech profile associated stored for a given user.

Thus, the system may be configured to record and make available forprocessing only the audio signals that are consistent with a biometricprofile, audio fingerprint, or other audio characteristics specificallystored in relation to a profile of a user who is registered with thesystem in question. Similarly, the face detection algorithm may onlyprovide an indication of success (and thus a trigger to record and makeavailable the audio signal) if the face detected is recognised as beinga user registered with the system.

In certain preferred embodiments, at least two of said additionalverification steps are performed.

The precise combination of verifications that are chosen for a givenapplication, or for a given set of circumstances or environmentalfactors, is at the discretion of the system designer, and may bedependent on factors such as the confidence with which one determinationwas made, the availability of a network connection, battery levels,system settings, the obligations imposed by data protection legislation,light levels, background noise levels, or any other factors.

In certain embodiments, the determination of the face detection and/orthe additional verification steps can be a weighted determinationindicative of the reliability of the determination in question, andwherein a positive determination is made when the weighted determinationis above a threshold.

Thus, a combination of verifications can be determined to meet athreshold based on a weighted sum or other combination of determinationresults. In this way a multi-factorial determination of user intentioncan be made even where one verification (e.g. face detection, gazetracking, audio input characteristics) is weaker than would normally beexpected.

Usefully, the face detection step may verify that the detected face isoriented in a predetermined direction or range of directions.

In other words, it may not be regarded as sufficient simply to determinethat a face was detected. It may also be regarded as a requirement in agiven application that the face is oriented towards the screen ortowards some other interface, or even towards a particular part of aroom or vehicle.

Suitably, the face detection step may verify that the visual input is ator below the level of the user's eyes or nose.

This is particularly useful in mobile device and handheld systems, wherein normal use the user may hold the device somewhere below the face, sothat e.g. a device-mounted camera detects nostrils. The detection ofnostrils may both provide a useful reference point for a face detectionalgorithm, and also a strong indicator that the detected face is that ofa user intending to interact with the device.

The method may include the step of performing said speech processingfunction on the recorded signal.

Alternatively or additionally, the method may include the step ofsending said recorded audio signal to a remote computing device forspeech processing.

Optionally, the method further includes the step of buffering said audiosignal, and (i) if a determination is made not to record and makeavailable the audio signal for speech processing, overwriting ordiscarding the buffered signal; and (ii) if a determination is made torecord and make available the audio signal for speech processing,retrieving said signal from the buffer.

Preferably, said buffer is of sufficient capacity to store an audiosignal of a duration at least as long as the time required to determinethe face detection and optionally the additional verification steps.

This is useful in avoiding “chopping” the start of the speech which theuser intended the device to capture, while it makes its verification.

Buffering in this way is to be distinguished from subsequently recordingand making available the audio signal in response to a positivedetermination.

More preferably, the buffer size is tailored to the required time (e.g.is chosen to fit 100% to 200% of the time period required on average fora successful verification to be established).

In another aspect there is provided a computerised system for processinguser input, comprising:

-   -   an audio input;    -   a visual input;    -   an interface to a storage medium suitable for recording audio        data;    -   an interface to a speech processing function;    -   an interface to an output, via which a visual or auditory prompt        may be provided to a user of the computing system; and    -   a processor programmed with instructions effective to cause said        system to:        -   control the output to provide a visual or prompt to a user            of the computing system;        -   perform a face detection method on an image received from            the visual input after the visual or auditory prompt has            been provided; and        -   responsive to a determination that said face detection            method has detected a face within a predetermined time of            the visual or auditory prompt having been provided:            -   record an audio signal from said audio input; and            -   make said audio signal available to a speech processing                function.

It will be appreciated that the computerised system, in preferredembodiments, may be programmed to implement the method of the preferredfeatures described above and in the dependent claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will now be further illustrated by the followingdescription of embodiments thereof, given by way of example only withreference to the accompanying drawings, in which:

FIG. 1 is a block architecture diagram of a computerised system forprocessing user input;

FIG. 2 is a flowchart of a first method of processing user input;

FIG. 3 is a flowchart of a second method of processing user input;

FIG. 4 is a flowchart of a third method of processing user input;

FIG. 5 is a flowchart of a fourth method of processing user input;

FIG. 6 is a flowchart of a fifth method of processing user input; and

FIG. 7 is a flowchart of a sixth method of processing user input.

In FIG. 1 there is indicated at 10 a computerised system for processinguser input. The system is implemented in a typical mobile handset orsmartphone but which has bespoke functionality programmed within an appor program 12 which can be executed on the device.

It will be understood that as with conventional devices, the system 10has a processor, a memory, and permanent storage, which are not shownbut upon which the functional components shown in FIG. 1 operate inknown manner under the overall control of an operating system 46 whichinteracts with the hardware via a plurality of physical controllers 48.

The device has a number of user input and output interfaces, typicallyincluding at least a microphone 14, speaker 16, camera 18 and atouchscreen 20, and also has a network interface 22 via which the devicecommunicates wirelessly with remote networks, devices and systems. Itwill be appreciated that the interfaces are simplified, and moderndevices may have many additional sensors, input and output devices, aswell as having a plurality of microphone, cameras, network interfaces ofdifferent kinds, etc. The details of such implementation will of coursebe utilised in any particular implementation but do not affect theunderlying basic operation of the invention as described herein.

For the evaluation of user inputs according to the invention, FIG. 1highlights two broad categories of signal processing, namely audioprocessing functions 24 and image or video processing 26. The designerof a system may choose to use dedicated processors for some or all ofthe functionality of audio and image/video processing or the processingmay be done on a general processor of the device.

The audio input signal from the microphone is directed to audioprocessing where it may be buffered if required in a circular buffer 28.Additional functionality provided in the audio processing may include anoise filter 30 to exclude or differentiate from non-speech orbackground noise and a speech detection function 32 which may detectwhether a given sound is or is not human speech. The speech detectionfunction can be as sophisticated as the hardware allows, depending onthe preferences of the system designer and the needs of the software.For example, while FIG. 1 shows that the primary speech processing 34occurs remotely, to allow for more powerful speech detection,transcription, speech verification, training of speech models, matchingagainst biometric patterns, etc., any or all of this functionality couldbe performed locally on the device.

Audio storage 36 may be provided locally on the device, in which audiodata can be stored either on a temporary basis until uploaded to aremote storage system 38 for longer term storage, or in which the datacan be stored locally on a long term basis. It will be appreciated thatthe choice of local/remote processing and storage will be driven by theneeds of the particular application, the capabilities of the systemsinvolved, and commercial factors.

The image/video processing subsystem 26 has a plurality of functionalmodules for processing and performing particular operations on imagesreceived from a visual input device such as camera 18. In particular inthe context of this disclosure a face detection function 40 is provided.

This face detection function can process an image or image stream tomake a determination whether it contains a face. It may performadditional checks such as matching the face against a user profiledatabase, checking that the face is detected at a particular size in theimage (and hence distance from the camera) or at a particular angle withrespect to the camera (such as that it is facing the camera, or that thecamera position relative to the face is consistent with an expectedposition in which a user would hold the device if wishing to interactwith it. The face detection function can output a binary decision (facedetected or not detected) or a more informative determination can bemade, including providing a multi-factorial determination (facedetected, user matched, user not facing camera, camera held in positionfor interaction), or a weighted score indicating the calculatedlikelihood of a valid match (i.e. that a face has been detected for auser likely to wish to interact according to data gleaned from theimage).

Also shown in the image processing subsystem 26 are an optional gazedetection module 42 and a mouth movement analysis module 44. The gazedetection module 42 operates in known manner to determine a gazedirection relative to the camera, which can be sufficiently precise todetermine that a user is looking at the device screen or some otherdisplay, or even that the user is looking at a certain part of thescreen or display (e.g. the user is looking at the prompt to speak). Themouth movement analysis module 44 can be provided as part of the facedetection function, or may receive inputs from the face detectionmodule. The mouth movement analysis module identifies if the mouth of auser is moving, and optionally, if the mouth is moving in a pattern thatis consistent with speaking. It may even identify if the movements areconsistent with speech expected from a prompt given to the user or fromother contextual information in the app (in other words, perform a formof lip reading from which user intent can be ascertained).

As will be now described in relation to FIGS. 2-7, the system of FIG. 1enables an indication of user intent to interact with the system to bedetermined and this determination to be used as the basis for a decisionto record and process speech or not.

FIGS. 2-7 describe several different implementations with differentdegrees of functionality but having certain core steps in common.Accordingly, where the same reference numerals are used in differentfigures, the reference is to the same function and it need not bedescribed again in the interests of avoiding undue repetition.

In FIG. 2, there is shown a method that operates on the system of FIG.1, although it could equally be implemented in any other computingsystem having access to an audio input, a visual input and a processorsuitably programmed to carry out the functionality now described. Themethod may be built into a larger app or program having voiceinteraction, or it can be provided as a standalone app, program, orsystem function.

In the description that follows it is assumed purely for putting theinvention in context that the method is provided as a built-in functionwithin a voice-interactive app such as an app to assist childrenlearning to read. Such an app may for example display words or sounds onscreen and wait for a child to read the words before continuing to a newscreen.

The user opens the app, step 50 and begins interacting with it in knownmanner. When the user is prompted to speak, step 52, the audio input isnot immediately recorded and processed upon display of the prompt, andnor is the user required to tap or hold a button to indicate anintention to speak to the app. Instead the face detection moduleprocesses images from the camera to determine if a face is detected,step 54, and possibly if the detection meets certain criteria (useridentified, face sufficiently close, angle of face correct, etc.). If nosatisfactory face detection is determined, the process of looking for aface continues until a timeout is reached, step 56, causing the user toagain be prompted (or the app could be programmed to move on, pause,prompt the user “are you still there?”, or save progress and close). Thetimeout can be linked to the prompt, e.g. if a visual prompt isdisplayed on a screen, then the face detection may remain active whilethe screen shows the prompt, or for a number of seconds after the promptis removed from the screen, or until a screen timeout occurs, or for anyother suitable time period.

If a face is detected meeting any criteria that may have been set, thispositive determination in step 54 causes the system to start recordingaudio, step 58. The audio can be simultaneously sent for localprocessing, step 60, for example by performing onboard speechrecognition, or it can be made available for processing by anotherprogram, device or system, such as by sending it via the networkinterface to a remote server which can process the speech and optionallyreturn results according to the outcome of the processing.

If an end condition is detected, step 62, the process reverts to step 52and the next prompt to speak. The end condition may be any conditionthat has been programmed as an indication that recording should stop.For example it could be the detection of silence indicating the user hasstopped speaking, or it may be a timeout (either a global defaulttimeout or a timeout that is dependent on the expected duration ofspeech according to the prompt, or it may arise from the user saying“stop” or similar commands, or from the speech processing engine (localor remote) returning a result (for example indicating that the prompthas been responded to correctly or not, when the speech is processed innear-real time) or the user making an intervention on the touchscreen,or a user gesture picked up by the camera, and so on.

It will be appreciated that using the method of FIG. 2, the decision torecord audio and to make the audio available for processing (includingoptionally the decision to start processing the audio) is arrived atmore intelligently and with a higher likelihood of being in accordancewith the user's intention. It furthermore is less prone to errorsarising from user inability to interact with the system or user error.

FIG. 3 shows a flowchart of a method that is similar in most respects tothat of FIG. 2 but having an additional verification step after a faceis detected in step 54. Following a positive determination in step 54,the gaze detection module verifies whether the user's eyes are directedat the screen. It may optionally require that the user's eyes aredirected to the part of the screen known to contain the prompt to speakin order to give a positive determination. If the determination isnegative, the process reverts to the timeout check 56. If thedetermination is positive, i.e. both conditions 54 and 64 are met, thenrecording starts 58 as before.

FIG. 4 shows an alternative implementation for the process of FIG. 3.The process of FIG. 4 differs from both FIGS. 2 and 3 in the addition ofa buffer. In step 66, after the user is prompted to speak, the systemstarts to record audio in a circular buffer, step 66. In this way, thesystem will have a few seconds of past audio continually in the bufferafter the prompt occurs. Any delay arising from a delay in facedetection 54 or gaze detection 64 can be compensated for, by retrievingthe audio from the buffer, step 68, and using the retrieved audio topopulate the start of the audio recording and the speech processing.Step 58′ is a modification of step 58 of FIGS. 2 and 3. Instead ofsimply starting recording in real time, an audio recording is populatedby the buffer contents and the recording function then adds the realtime audio stream on to the end of this file.

The buffer also allows the system to catch up if, for example the userbegins to speak just before turning to or looking at the system (e.g. ifprompted aurally rather than or in addition to visually).

FIG. 5 shows a method similar to that of FIG. 4, but with the inclusionof an additional verification condition after face detection step 54 andin parallel with the gaze detection step 64. In step 70, the mouthanalysis movement function verifies whether the user's mouth is moving,and optionally whether it is moving in a pattern consistent with speech(or even with the expected words). If the determinations are allpositive, step 72, then the process proceeds as before. If not, thesystem reverts to the timeout check 56. It is possible that a flag ispassed back for each of the verification steps, for example to indicatethat a face has been detected, and that it has looked at the prompt, butwith a negative flag for mouth movement. Then on a subsequent loop, thesystem will only look for the mouth movement flag to be changed. This isuseful to cater for the fact that sometimes a user will be prompted e.g.for a translation or an answer to a question (and will look to thescreen for the prompt). Depending on the user, they may look away e.g.lok up or close their eyes) while they try to figure out the appropriateresponse. Therefore at the time of answering, they may no longer belooking at the screen.

FIG. 6 is a modification of FIG. 5, with the addition of a furtherparallel additional verification step, namely a check whether audio isdetected at the microphone, step 74. If all of the determinations,including step 74 are true, the recording begins, similar to FIG. 5.

FIG. 7 is a modification of FIG. 6, wherein if audio is detected in step74, it is further processed to determine if it is consistent withspeech, step 76. This can eliminate spurious recordings of externalnoises, coughing, laughter, etc.

While FIGS. 3-7 show that the face detection step occurs prior to anyadditional verification steps, this need not be the case. Thedeterminations can be in any order, or can be simultaneous orindependent of one another. Similarly, while FIGS. 5-7 show a pluralityof additional verification steps in parallel to one another, they neednot be in parallel and can be in any order or no order with respect toeach other and to the face detection step.

The precise combinations of verification steps (face and eyes in FIGS. 3and 4; face, eyes and mouth in FIG. 5; face, eyes, mouth and audio inFIG. 6; face, eyes, mouth, audio and speech in FIG. 7) are in no waylimiting. The combination of face detection with any additionalverification step or combination of verification steps, is envisaged.For example, if no gaze detection function is available or there is nomouth movement analysis function available, the system might beprogrammed to perform face detection and the presence of an audio inputof suitable frequency, and use this combination to determine whether tostart recording and to make the audio available for processing.

1. A method of processing user input to a computing system having anaudio input and a visual input, the method comprising: receiving, at thecomputing system, the audio input; determining whether the user hasdemonstrated an intent to interact with the computing system via theaudio input, wherein determining whether the user has demonstrated theintent to interact with the computing system via the audio inputcomprises: performing a face detection method on an image received fromthe visual input after the audio input has been received; anddetermining whether said face detection method has detected a facewithin a predetermined time of the audio input having been received; andresponsive to determining that the user has demonstrated the intent tointeract with the computing system: recording an audio signal from saidaudio input; and making said audio signal available to a speechprocessing function.
 2. The method of claim 1, further comprisingperforming one or more additional verification operations, whereinrecording the audio signal and making said audio signal available aredependent on the outcome of said one or more further verificationoperations in addition to said face detection method detecting a face.3. The method of claim 2, wherein said one or more additionalverification operations comprise a gaze direction detection operation toverify that the user is looking in a predefined direction or range ofdirections.
 4. The method of claim 2, wherein said one or moreadditional verification operations comprise a mouth movement detectionoperation to verify that the user's mouth is moving.
 5. The method ofclaim 4, wherein said mouth movement detection operation furtherverifies that the mouth movement of the user corresponds to a movementpattern typical of speech.
 6. The method of claim 2, wherein said one ormore additional verification operations comprise an audio detectionoperation to verify that the audio input is receiving sound from theenvironment of the user.
 7. The method of claim 6, wherein said audiodetection operation further verifies that the characteristics ofdetected sound are consistent with speech.
 8. The method of claim 6,wherein said audio detection operation further verifies that thedirection from which sound is detected is consistent with the directionof the detected face.
 9. The method of claim 6, wherein said audiodetection operation further verifies that the characteristics ofdetected sound are consistent with a speech profile stored for a givenuser.
 10. The method of claim 2, wherein at least two of said additionalverification operations are performed.
 11. The method of claim 2,wherein the determination of the face detection and/or the additionalverification operations is a weighted determination indicative of thereliability of the determination in question, and wherein a positivedetermination is made when the weighted determination is above athreshold.
 12. The method of claim 1, wherein said face detectionoperation verifies that the detected face is oriented in a predetermineddirection or range of directions.
 13. The method of claim 11, whereinthe face detection operation verifies that the visual input is at orbelow the level of the user's eyes or nose.
 14. The method of claim 1,further comprising performing said speech processing function on therecorded signal.
 15. The method of claim 1, further comprising sendingsaid recorded audio signal to a remote computing device for speechprocessing.
 16. The method of claim 1, further comprising buffering saidaudio signal, and (i) responsive to determining that the user hasdemonstrated the intent to interact with the computing system,overwriting or discarding the buffered signal; and (ii) responsive todetermining that the user has demonstrated the intent to interact withthe computing system, retrieving said signal from the buffer.
 17. Themethod of claim 15, wherein said buffer is of sufficient capacity tostore an audio signal of a duration at least as long as the timerequired to determine the face detection and optionally the additionalverification operations.
 18. A computing system for processing userinput having an audio input and a visual input, the system comprising: amemory; and a processor, coupled to the memory, to: receive, at thecomputing system, the audio input; determine whether the user hasdemonstrated an intent to interact with the computing system via theaudio input, wherein to determine whether the user has demonstrated theintent to interact with the computing system via the audio input, theprocessor is further to: perform a face detection method on an imagereceived from the visual input after the audio input has been received;and determine whether said face detection method has detected a facewithin a predetermined time of the audio input having been received; andresponsive to determining that the user has demonstrated the intent tointeract with the computing system: record an audio signal from saidaudio input; and make said audio signal available to a speech processingfunction.
 19. A non-transitory computer readable medium comprisinginstructions, which when executed by a processor, cause the processor toperform a method of processing user input to a computing system havingan audio input and a visual input, the method comprising: receiving, atthe computing system, the audio input; determining whether the user hasdemonstrated an intent to interact with the computing system via theaudio input, wherein determining whether the user has demonstrated theintent to interact with the computing system via the audio inputcomprises: performing a face detection method on an image received fromthe visual input after the audio input has been received; anddetermining whether said face detection method has detected a facewithin a predetermined time of the audio input having been received; andresponsive to determining that the user has demonstrated the intent tointeract with the computing system: recording an audio signal from saidaudio input; and making said audio signal available to a speechprocessing function.
 20. The non-transitory computer readable medium ofclaim 19, wherein the method further comprises performing one or moreadditional verification operations, wherein recording the audio signaland making said audio signal available are dependent on the outcome ofsaid one or more further verification operations in addition to saidface detection method detecting a face.